Enhanced filters in a wireless communication system

ABSTRACT

Apparatuses, methods, and systems are disclosed for enhanced measurements and filters. One apparatus includes a receiver that detects a reference signal during a first time window of a set of time windows during which reception of the reference signal is expected and detects the reference signal during a second time window of the set of time windows. In various embodiments, the second time window occurs an offset time after the first time window. In some embodiments, the apparatus includes a processor that determines a filter coefficient based on the offset time. In such embodiments, the filter coefficient is used to generate a filtered measurement.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Patent ApplicationNo. 62/233,086 entitled “ENHANCED MEASUREMENTS AND FILTERS IN A WIRELESSCOMMUNICATION SYSTEM” and filed on Sep. 25, 2015 which is incorporatedherein by reference in its entirety.

FIELD

The subject matter disclosed herein relates generally to wirelesscommunications and more particularly relates to enhanced measurementsand filters in a wireless communication system.

BACKGROUND

The following abbreviations are herewith defined, at least some of whichare referred to within the following description.

3GPP Third Generation Partnership Project

ACK Positive-Acknowledgment

BLER Block Error Ratio

BPSK Binary Phase Shift Keying

C-RNTI Cell Radio Network Temporary Identifier

CAZAC Constant Amplitude Zero Auto Correction

CCA Clear Channel Assessment

CCE Control Channel Element

CDF Cumulative Distribution Function

CP Cyclic Prefix

CQI Channel Quality Information

CSI Channel State Information

CSS Common Search Space

CWS Contention Window Size

DCI Downlink Control Information

DL Downlink

DMTC Discover Signal Measurement Timing Configuration

DRX Discontinuous Reception

eCCA Enhanced Clear Channel Assessment

eNB Evolved Node B

EPDCCH Enhanced Physical Downlink Control Channel

ETSI European Telecommunications Standards Institute

FBE Frame Based Equipment

FDD Frequency Division Duplex

FDMA Frequency Division Multiple Access

FEC Forward Error Correction

HARQ Hybrid Automatic Repeat Request

LAA Licensed Assisted Access

LAA-RSSI Licensed Assisted Access Received Signal Strength Indicator

LBE Load Based Equipment

LBT Listen-Before-Talk

LTE Long Term Evolution

MAC Medium Access Control

MCL Minimum Coupling Loss

MCS Modulation and Coding Scheme

MU-MIMO Multi-User, Multiple-Input, Multiple-Output

NACK or NAK Negative-Acknowledgment

OFDM Orthogonal Frequency Division Multiplexing

PCell Primary Cell

PCID Physical Cell ID

PBCH Physical Broadcast Channel

PDCCH Physical Downlink Control Channel

PDSCH Physical Downlink Shared Channel

PHICH Physical Hybrid ARQ Indicator Channel

PLMN Public Land Mobile Network

PRACH Physical Random Access Channel

PRB Physical Resource Block

PUCCH Physical Uplink Control Channel

PUSCH Physical Uplink Shared Channel

RNTI Radio Network Temporary Identifier

QoS Quality of Service

QPSK Quadrature Phase Shift Keying

RAR Random Access Response

RRC Radio Resource Control

RRM Radio Resource Management

RSRP Reference Signal Received Power

RSRQ Reference Signal Received Quality

RSSI Received Signal Strength Indicator

RX Receive

SC-FDMA Single Carrier Frequency Division Multiple Access

SCell Secondary Cell

SCH Shared Channel

SFN System Frequency Number

SIB System Information Block

SNR Signal-to-Interference-Plus-Noise Ratio

SR Scheduling Request

TBS Transport Block Size

TDD Time-Division Duplex

TDM Time Division Multiplex

TX Transmit

UCI Uplink Control Information

UE User Entity/Equipment (Mobile Terminal)

UL Uplink

UMTS Universal Mobile Telecommunications System

VoIP Voice Over Internet Protocol

WiMAX Worldwide Interoperability for Microwave Access

In wireless communications networks, LAA facilitates an LTE system touse an unlicensed spectrum with assistance from a licensed carrier. LAAfurther aims to facilitate the fair coexistence with other technologiesover the unlicensed spectrum and to satisfy various regulatoryrequirements in different countries and regions. In certainconfigurations, LAA operations may depend heavily on the LBT procedure.For example, if a channel is occupied, an eNB cannot transmit on thatchannel.

As may be appreciated, if a carrier has a significant amount of activityfrom other nodes (e.g., Wi-Fi, LAA, etc.) transmissions may be delayed.The delay of transmissions may apply to all transmissions includingdiscovery signal transmissions, which are used for RRM measurements. Theunpredictability of discovery signal transmissions may lead to variousproblems.

For example, RSRP measurements for LAA may be performed based onmeasurements of discovery signals. In one embodiment, a UE is provided aDMTC configuration, from which the UE derives time windows during whichit expects to detect a discovery signal transmission. However,transmissions of discovery signals may be subject to the LBT procedure.Thus, if the channel is occupied, during the DMTC window, the discoverysignal transmission is delayed or skipped. It should be noted that theDMTC window may be kept small to ensure that the UE power consumptionfor detecting and measuring the discovery signals remains manageable. Ifa discovery signal transmission is skipped or delayed, the UE physicallayer may not provide a corresponding physical layer measurement to RRC.

A delay or skip in discovery signal transmissions by an eNB implies adelay in RSRP measurement samples by a UE. In various configurations,the UE may perform layer 3 filtering of physical layer RSRPmeasurements. The layer 3 filtering in LTE assumes that a measurementsample is made available at least once every 200 milliseconds (“ms”). Ifa discovery signal is considerably delayed, channel conditions may havechanged significantly by the time the discovery signal is actuallytransmitted. However, a history in a layer 3 filter may cause theconvergence of the filtered measurements to the new channel conditionsto be slow.

Furthermore, RSRP measurements may not give a clear picture of activityon a carrier. In certain configurations, a UE may find a carrier thathas a desired LAA cell (e.g., belonging to desired PLMN) and measure ahigh RSRP for the cell. On a different carrier the UE may find a desiredLAA cell and measure a moderate RSRP for the cell. Based on the currentmeasurement framework, the first cell would be chosen for LAA service.However, if the first carrier has a significantly higher level ofactivity/channel occupancy compared to the second carrier, thethroughput that can be achieved on the first cell may be lower than thethroughput that can be achieved on the second cell. Moreover, forcertain types of services (e.g., VoIP and other periodic packet arrivalservices) a carrier with low occupancy may be preferred.

BRIEF SUMMARY

Apparatuses for enhanced measurements and filters are disclosed. Methodsand systems also perform the functions of the apparatus. In oneembodiment, the apparatus includes a receiver that detects a referencesignal during a first time window of a set of time windows during whichreception of the reference signal is expected and detects the referencesignal during a second time window of the set of time windows. Invarious embodiments, the second time window occurs an offset time afterthe first time window. In some embodiments, the apparatus includes aprocessor that determines a filter coefficient based on the offset time.In such embodiments, the filter coefficient is used to generate afiltered measurement.

In one embodiment, the offset time includes one or more time windows ofthe set of time windows during which the reference signal is notdetected. In a further embodiment, the processor determines the filtercoefficient by summing a predetermined filter coefficient and aparameter derived as a function of the offset time. In some embodiments,the processor determines the filter coefficient to be a first value ifthe offset time is less than a threshold time and to be a second valueif the offset time is greater than or equal to the threshold time.

A method for enhanced measurements and filters, in one embodiment,includes detecting, by use of a receiver, a reference signal during afirst time window of a set of time windows during which reception of thereference signal is expected. In various embodiments, the method mayinclude detecting the reference signal during a second time window ofthe set of time windows. In such embodiments, the second time windowoccurs an offset time after the first time window. In some embodiments,the method includes determining a filter coefficient based on the offsettime. In such embodiments, the filter coefficient is used to generate afiltered measurement.

In one embodiment, the offset time includes one or more time windows ofthe set of time windows during which the reference signal is notdetected. In a further embodiment, determining the filter coefficientbased on the offset time includes determining the filter coefficient bysumming a predetermined filter coefficient and a parameter derived as afunction of the offset time. In some embodiments, determining the filtercoefficient based on the offset time includes determining the filtercoefficient to be a first value if the offset time is less than athreshold time and to be a second value if the offset time is greaterthan or equal to the threshold time.

Another method for enhanced measurements and filters, in one embodiment,includes performing, by use of a processor, a first measurement at afirst time. In various embodiments, the method may include determiningan offset time selected pseudo-randomly from a set of values. In someembodiments, the method includes performing a second measurement at asecond time, the second time being the offset time after the first time.In such embodiments, the second measurement is used for a carrierloading measurement.

In certain embodiments, determining the offset time selectedpseudo-randomly from the set of values includes determining the offsettime based on at least one of a subframe index, a system frame number, acell radio network temporary identifier (“C-RNTI”), a physical cell id,a virtual cell id, and a scrambling sequence initialization value. Insome embodiments, determining the offset time selected pseudo-randomlyfrom the set of values includes determining the offset time based on amodulo function with at least one of the following inputs: a subframeindex, a system frame number, a cell radio network temporary identifier(“C-RNTI”), a physical cell id, a virtual cell id, and a scramblingsequence initialization value.

In one embodiment, an apparatus includes a receiver that receivesinformation. In various embodiments, the apparatus may include aprocessor that performs a first measurement in a first set of subframesreceived by the receiver at a first time. In such embodiments, the firstset of subframes includes at least one subframe. In some embodiments,the processor performs a second measurement in a second set of subframesreceived by the receiver at a second time. In such embodiments, thesecond set of subframes includes at least one subframe. In variousembodiments, the second set of subframes is offset in time from thefirst set of subframes by an offset time, the offset time beingdetermined using a pseudo-random function.

In various embodiments, the pseudo-random function determines the offsettime based on at least one of a subframe index, a system frame number, acell radio network temporary identifier (“C-RNTI”), a physical cell id,a virtual cell id, and a scrambling sequence initialization value. Inone embodiment, the first measurement is a reference signal receivedpower (“RSRP”) measurement and the second measurement is a carrierloading measurement. In certain embodiments, the first measurementoccurs in a discovery signal measurement timing configuration (“DMTC”)time window and the second measurement occurs outside of a DMTC timewindow.

Another method for enhanced measurements and filters, in one embodiment,includes performing, by use of a processor, a first measurement in afirst set of subframes at a first time. In such an embodiment, the firstset of subframes includes at least one subframe. In various embodiments,the method includes performing a second measurement in a second set ofsubframes at a second time. In such embodiments, the second set ofsubframes includes at least one subframe. In various embodiments, thesecond set of subframes is offset in time from the first set ofsubframes by an offset time, the offset time being determined using apseudo-random function.

In one embodiment, the pseudo-random function determines the offset timebased on at least one of a subframe index, a system frame number, a cellradio network temporary identifier (“C-RNTI”), a physical cell id, avirtual cell id, and a scrambling sequence initialization value. Inanother embodiment, the first measurement is a reference signal receivedpower (“RSRP”) measurement and the second measurement is a carrierloading measurement. In some embodiments, the first measurement occursin a discovery signal measurement timing configuration (“DMTC”) timewindow and the second measurement occurs outside of a DMTC time window.

In one embodiment, an apparatus includes a receiver that receivesinformation corresponding to load measurements made by a device. In suchan embodiment, wherein the load measurements include a first measurementin a first set of subframes at a first time, wherein the first set ofsubframes include at least one subframe, a second measurement in asecond set of subframes at a second time, wherein the second set ofsubframes include at least one subframe, and wherein the second set ofsubframes is offset in time from the first set of subframes by an offsettime, the offset time being determined using a pseudo-random function.In various embodiments, the apparatus includes a processor thatdetermines carriers to be used based on the information.

In certain embodiments, the first measurement is a reference signalreceived power (“RSRP”) measurement and the second measurement is acarrier loading measurement. In some embodiments, the first measurementoccurs in a discover signal measurement timing configuration (“DMTC”)time window and the second measurement occurs outside of a DMTC timewindow.

A further method for enhanced measurements and filters, in oneembodiment, includes receiving, by use of a receiver, informationcorresponding to load measurements made by a device. In such anembodiment, the load measurements include a first measurement in a firstset of subframes at a first time, wherein the first set of subframesinclude at least one subframe, a second measurement in a second set ofsubframes at a second time, wherein the second set of subframes includeat least one subframe, and wherein the second set of subframes is offsetin time from the first set of subframes by an offset time, the offsettime being determined using a pseudo-random function. In variousembodiments, the method includes determining carriers to be used basedon the information.

In certain embodiments, the first measurement is a reference signalreceived power (“RSRP”) measurement and the second measurement is acarrier loading measurement. In some embodiments, the first measurementoccurs in a discover signal measurement timing configuration (“DMTC”)time window and the second measurement occurs outside of a DMTC timewindow.

Another method for enhanced measurements and filters, in one embodiment,includes receiving, by use of a receiver, a discovery signal measurementtiming configuration (“DMTC”) from higher layer signaling. In variousembodiments, the method includes determining a set of periodic DMTC timewindows from the received DMTC, wherein each periodic DMTC time windowof the set of periodic DMTC time windows includes a set of contiguoussubframes. In one embodiment, the method includes determining a set ofcarrier loading measurement time windows, wherein each carrier loadingmeasurement time window of the set of carrier loading measurement timewindows includes a set of contiguous subframes. In certain embodiments,the method includes measuring carrier loading in at least one subframein each carrier loading measurement time window of the set of carrierloading measurement time windows. In one embodiment, each carrierloading measurement time window of the set of the carrier loadingmeasurement time windows occur immediately adjacent in time to arespective periodic DMTC time window of the set of periodic DMTC timewindows and each carrier loading measurement time window does notoverlap its respective periodic DMTC time window.

In one embodiment, the method includes measuring at least one ofreference signal received power (“RSRP”) and reference signal receivedquality (“RSRQ”) in at least one subframe of each periodic DMTC timewindow of the set of periodic DMTC time windows. In various embodiments,each carrier loading measurement time window of the set of carrierloading measurement time windows is a periodic carrier loadingmeasurement time window. In some embodiments, a carrier loadingmeasurement time window periodicity is a multiple of a DMTC time windowperiodicity.

BRIEF DESCRIPTION OF THE DRAWINGS

A more particular description of the embodiments briefly described abovewill be rendered by reference to specific embodiments that areillustrated in the appended drawings. Understanding that these drawingsdepict only some embodiments and are not therefore to be considered tobe limiting of scope, the embodiments will be described and explainedwith additional specificity and detail through the use of theaccompanying drawings, in which:

FIG. 1 is a schematic block diagram illustrating one embodiment of awireless communication system for enhanced measurements and filters;

FIG. 2 is a schematic block diagram illustrating one embodiment of anapparatus that may be used for enhanced measurements and filters;

FIG. 3 is a schematic block diagram illustrating another embodiment ofan apparatus that may be used for enhanced measurements and filters;

FIG. 4 illustrates a graph of one embodiment of layer 3 filtering;

FIG. 5 illustrates a graph of another embodiment of layer 3 filtering;

FIG. 6 illustrates a graph of a further embodiment of layer 3 filtering;

FIG. 7 illustrates a graph of various embodiments of measurementadaptations;

FIG. 8 is a schematic flow chart diagram illustrating one embodiment ofa method for enhanced filtering;

FIG. 9 is a schematic flow chart diagram illustrating one embodiment ofa method for enhanced measurements;

FIG. 10 is a schematic flow chart diagram illustrating anotherembodiment of a method for enhanced measurements;

FIG. 11 is a schematic flow chart diagram illustrating one embodiment ofa method for carrier determination; and

FIG. 12 is a schematic flow chart diagram illustrating a furtherembodiment of a method for enhanced measurements.

DETAILED DESCRIPTION

As will be appreciated by one skilled in the art, aspects of theembodiments may be embodied as a system, apparatus, method, or programproduct. Accordingly, embodiments may take the form of an entirelyhardware embodiment, an entirely software embodiment (includingfirmware, resident software, micro-code, etc.) or an embodimentcombining software and hardware aspects that may all generally bereferred to herein as a “circuit,” “module” or “system.” Furthermore,embodiments may take the form of a program product embodied in one ormore computer readable storage devices storing machine readable code,computer readable code, and/or program code, referred hereafter as code.The storage devices may be tangible, non-transitory, and/ornon-transmission. The storage devices may not embody signals. In acertain embodiment, the storage devices only employ signals foraccessing code.

Certain of the functional units described in this specification may belabeled as modules, in order to more particularly emphasize theirimplementation independence. For example, a module may be implemented asa hardware circuit comprising custom very-large-scale integration(“VLSI”) circuits or gate arrays, off-the-shelf semiconductors such aslogic chips, transistors, or other discrete components. A module mayalso be implemented in programmable hardware devices such as fieldprogrammable gate arrays, programmable array logic, programmable logicdevices or the like.

Modules may also be implemented in code and/or software for execution byvarious types of processors. An identified module of code may, forinstance, include one or more physical or logical blocks of executablecode which may, for instance, be organized as an object, procedure, orfunction. Nevertheless, the executables of an identified module need notbe physically located together, but may include disparate instructionsstored in different locations which, when joined logically together,include the module and achieve the stated purpose for the module.

Indeed, a module of code may be a single instruction, or manyinstructions, and may even be distributed over several different codesegments, among different programs, and across several memory devices.Similarly, operational data may be identified and illustrated hereinwithin modules, and may be embodied in any suitable form and organizedwithin any suitable type of data structure. The operational data may becollected as a single data set, or may be distributed over differentlocations including over different computer readable storage devices.Where a module or portions of a module are implemented in software, thesoftware portions are stored on one or more computer readable storagedevices.

Any combination of one or more computer readable medium may be utilized.The computer readable medium may be a computer readable storage medium.The computer readable storage medium may be a storage device storing thecode. The storage device may be, for example, but not limited to, anelectronic, magnetic, optical, electromagnetic, infrared, holographic,micromechanical, or semiconductor system, apparatus, or device, or anysuitable combination of the foregoing.

More specific examples (a non-exhaustive list) of the storage devicewould include the following: an electrical connection having one or morewires, a portable computer diskette, a hard disk, a random access memory(“RAM”), a read-only memory (“ROM”), an erasable programmable read-onlymemory (“EPROM” or Flash memory), a portable compact disc read-onlymemory (“CD-ROM”), an optical storage device, a magnetic storage device,or any suitable combination of the foregoing. In the context of thisdocument, a computer readable storage medium may be any tangible mediumthat can contain, or store a program for use by or in connection with aninstruction execution system, apparatus, or device.

Code for carrying out operations for embodiments may be any number oflines and may be written in any combination of one or more programminglanguages including an object oriented programming language such asPython, Ruby, Java, Smalltalk, C++, or the like, and conventionalprocedural programming languages, such as the “C” programming language,or the like, and/or machine languages such as assembly languages. Thecode may execute entirely on the user's computer, partly on the user'scomputer, as a stand-alone software package, partly on the user'scomputer and partly on a remote computer or entirely on the remotecomputer or server. In the latter scenario, the remote computer may beconnected to the user's computer through any type of network, includinga local area network (“LAN”) or a wide area network (“WAN”), or theconnection may be made to an external computer (for example, through theInternet using an Internet Service Provider).

Reference throughout this specification to “one embodiment,” “anembodiment,” or similar language means that a particular feature,structure, or characteristic described in connection with the embodimentis included in at least one embodiment. Thus, appearances of the phrases“in one embodiment,” “in an embodiment,” and similar language throughoutthis specification may, but do not necessarily, all refer to the sameembodiment, but mean “one or more but not all embodiments” unlessexpressly specified otherwise. The terms “including,” “comprising,”“having,” and variations thereof mean “including but not limited to,”unless expressly specified otherwise. An enumerated listing of itemsdoes not imply that any or all of the items are mutually exclusive,unless expressly specified otherwise. The terms “a,” “an,” and “the”also refer to “one or more” unless expressly specified otherwise.

Furthermore, the described features, structures, or characteristics ofthe embodiments may be combined in any suitable manner. In the followingdescription, numerous specific details are provided, such as examples ofprogramming, software modules, user selections, network transactions,database queries, database structures, hardware modules, hardwarecircuits, hardware chips, etc., to provide a thorough understanding ofembodiments. One skilled in the relevant art will recognize, however,that embodiments may be practiced without one or more of the specificdetails, or with other methods, components, materials, and so forth. Inother instances, well-known structures, materials, or operations are notshown or described in detail to avoid obscuring aspects of anembodiment.

Aspects of the embodiments are described below with reference toschematic flowchart diagrams and/or schematic block diagrams of methods,apparatuses, systems, and program products according to embodiments. Itwill be understood that each block of the schematic flowchart diagramsand/or schematic block diagrams, and combinations of blocks in theschematic flowchart diagrams and/or schematic block diagrams, can beimplemented by code. These code may be provided to a processor of ageneral purpose computer, special purpose computer, or otherprogrammable data processing apparatus to produce a machine, such thatthe instructions, which execute via the processor of the computer orother programmable data processing apparatus, create means forimplementing the functions/acts specified in the schematic flowchartdiagrams and/or schematic block diagrams block or blocks.

The code may also be stored in a storage device that can direct acomputer, other programmable data processing apparatus, or other devicesto function in a particular manner, such that the instructions stored inthe storage device produce an article of manufacture includinginstructions which implement the function/act specified in the schematicflowchart diagrams and/or schematic block diagrams block or blocks.

The code may also be loaded onto a computer, other programmable dataprocessing apparatus, or other devices to cause a series of operationalsteps to be performed on the computer, other programmable apparatus orother devices to produce a computer implemented process such that thecode which execute on the computer or other programmable apparatusprovide processes for implementing the functions/acts specified in theflowchart and/or block diagram block or blocks.

The schematic flowchart diagrams and/or schematic block diagrams in theFigures illustrate the architecture, functionality, and operation ofpossible implementations of apparatuses, systems, methods and programproducts according to various embodiments. In this regard, each block inthe schematic flowchart diagrams and/or schematic block diagrams mayrepresent a module, segment, or portion of code, which includes one ormore executable instructions of the code for implementing the specifiedlogical function(s).

It should also be noted that, in some alternative implementations, thefunctions noted in the block may occur out of the order noted in theFigures. For example, two blocks shown in succession may, in fact, beexecuted substantially concurrently, or the blocks may sometimes beexecuted in the reverse order, depending upon the functionalityinvolved. Other steps and methods may be conceived that are equivalentin function, logic, or effect to one or more blocks, or portionsthereof, of the illustrated Figures.

Although various arrow types and line types may be employed in theflowchart and/or block diagrams, they are understood not to limit thescope of the corresponding embodiments. Indeed, some arrows or otherconnectors may be used to indicate only the logical flow of the depictedembodiment. For instance, an arrow may indicate a waiting or monitoringperiod of unspecified duration between enumerated steps of the depictedembodiment. It will also be noted that each block of the block diagramsand/or flowchart diagrams, and combinations of blocks in the blockdiagrams and/or flowchart diagrams, can be implemented by specialpurpose hardware-based systems that perform the specified functions oracts, or combinations of special purpose hardware and code.

The description of elements in each figure may refer to elements ofproceeding figures. Like numbers refer to like elements in all figures,including alternate embodiments of like elements.

FIG. 1 depicts an embodiment of a wireless communication system 100 forenhanced measurements and filters. In one embodiment, the wirelesscommunication system 100 includes remote units 102, base units 104, andunlicensed carriers 106. Even though a specific number of remote units102, base units 104, and unlicensed carriers 106 are depicted in FIG. 1,one of skill in the art will recognize that any number of remote units102, base units 104, and unlicensed carriers 106 may be included in thewireless communication system 100.

In one embodiment, the remote units 102 may include computing devices,such as desktop computers, laptop computers, personal digital assistants(“PDAs”), tablet computers, smart phones, smart televisions (e.g.,televisions connected to the Internet), set-top boxes, game consoles,security systems (including security cameras), vehicle on-boardcomputers, network devices (e.g., routers, switches, modems), or thelike. In some embodiments, the remote units 102 include wearabledevices, such as smart watches, fitness bands, optical head-mounteddisplays, or the like. Moreover, the remote units 102 may be referred toas subscriber units, mobiles, mobile stations, users, terminals, mobileterminals, fixed terminals, subscriber stations, UE, user terminals, adevice, or by other terminology used in the art. The remote units 102may communicate directly with one or more of the base units 104 via ULcommunication signals.

The base units 104 may be distributed over a geographic region. Incertain embodiments, a base unit 104 may also be referred to as anaccess point, an access terminal, a base, a base station, a Node-B, aneNB, a Home Node-B, a relay node, a device, or by any other terminologyused in the art. The base units 104 are generally part of a radio accessnetwork that includes one or more controllers communicably coupled toone or more corresponding base units 104. The radio access network isgenerally communicably coupled to one or more core networks, which maybe coupled to other networks, like the Internet and public switchedtelephone networks, among other networks. These and other elements ofradio access and core networks are not illustrated but are well knowngenerally by those having ordinary skill in the art.

In one implementation, the wireless communication system 100 iscompliant with the LTE of the 3GPP protocol, wherein the base unit 104transmits using an OFDM modulation scheme on the DL and the remote units102 transmit on the UL using a SC-FDMA scheme. More generally, however,the wireless communication system 100 may implement some other open orproprietary communication protocol, for example, WiMAX, among otherprotocols. The present disclosure is not intended to be limited to theimplementation of any particular wireless communication systemarchitecture or protocol.

The base units 104 may serve a number of remote units 102 within aserving area, for example, a cell or a cell sector via a wirelesscommunication link. The base units 104 transmit DL communication signalsto serve the remote units 102 in the time, frequency, and/or spatialdomain. The unlicensed carriers 106 may be any suitable unlicensedcarrier, such as a Wi-Fi access point (“AP”). The unlicensed carriers106 may communicate with one or more of the remote units 102.

In certain embodiments, a remote unit 102 (e.g., device) may detect areference signal during a first time window of a set of time windowsduring which reception of the reference signal is expected and detectthe reference signal during a second time window of the set of timewindows. The second time window may occur an offset time after the firsttime window. The remote unit 102 may also determine a filter coefficientbased on the offset time. The filter coefficient may be used to generatea filtered measurement. Accordingly, the filtered measurement may bemore suitable for operation than in configurations that do not changethe filter coefficient based on the offset time.

In one embodiment, a remote unit 102 (e.g., device) may perform a firstmeasurement at a first time. The remote unit 102 may determine an offsettime selected pseudo-randomly from a set of values. As may beappreciated, pseudo-random may refer to something that appears random,but is not. For example, pseudo-random sequences may exhibit statisticalrandomness but are generated by an entirely deterministic causalprocess. Moreover, the remote unit 102 may perform a second measurementat a second time, the second time being the offset time after the firsttime. The second measurement may be used for a carrier loadingmeasurement. A base unit 104 (e.g., device) may receive the informationfrom the remote unit 102 corresponding to load measurements and maydetermine carriers to be used based on the information.

FIG. 2 depicts one embodiment of an apparatus 200 that may be used forenhanced measurements and filters. The apparatus 200 includes oneembodiment of the remote unit 102. Furthermore, the remote unit 102 mayinclude a processor 202, a memory 204, an input device 206, a display208, a transmitter 210, and a receiver 212. In some embodiments, theinput device 206 and the display 208 are combined into a single device,such as a touchscreen. In certain embodiments, the remote unit 102 maynot include any input device 206 and/or display 208. In variousembodiments, the remote unit 102 may include one or more of theprocessor 202, the memory 204, the transmitter 210, and the receiver212, and may not include the input device 206 and/or the display 208.

The processor 202, in one embodiment, may include any known controllercapable of executing computer-readable instructions and/or capable ofperforming logical operations. For example, the processor 202 may be amicrocontroller, a microprocessor, a central processing unit (“CPU”), agraphics processing unit (“GPU”), an auxiliary processing unit, a fieldprogrammable gate array (“FPGA”), or similar programmable controller. Insome embodiments, the processor 202 executes instructions stored in thememory 204 to perform the methods and routines described herein. Theprocessor 202 is communicatively coupled to the memory 204, the inputdevice 206, the display 208, the transmitter 210, and the receiver 212.In certain embodiments, the processor 202 may determine a filtercoefficient based on an offset time, wherein the filter coefficient isused to generate a filtered measurement. In some embodiments, theprocessor 202 may perform a first measurement in a first set ofsubframes received by a receiver at a first time and may perform asecond measurement in a second set of subframes received by the receiverat a second time.

The memory 204, in one embodiment, is a computer readable storagemedium. In some embodiments, the memory 204 includes volatile computerstorage media. For example, the memory 204 may include a RAM, includingdynamic RAM (“DRAM”), synchronous dynamic RAM (“SDRAM”), and/or staticRAM (“SRAM”). In some embodiments, the memory 204 includes non-volatilecomputer storage media. For example, the memory 204 may include a harddisk drive, a flash memory, or any other suitable non-volatile computerstorage device. In some embodiments, the memory 204 includes bothvolatile and non-volatile computer storage media. In some embodiments,the memory 204 stores data relating to filter coefficients,configuration information, and so forth. In some embodiments, the memory204 also stores program code and related data, such as an operatingsystem or other controller algorithms operating on the remote unit 102.

The input device 206, in one embodiment, may include any known computerinput device including a touch panel, a button, a keyboard, a stylus, amicrophone, or the like. In some embodiments, the input device 206 maybe integrated with the display 208, for example, as a touchscreen orsimilar touch-sensitive display. In some embodiments, the input device206 includes a touchscreen such that text may be input using a virtualkeyboard displayed on the touchscreen and/or by handwriting on thetouchscreen. In some embodiments, the input device 206 includes two ormore different devices, such as a keyboard and a touch panel.

The display 208, in one embodiment, may include any known electronicallycontrollable display or display device. The display 208 may be designedto output visual, audible, and/or haptic signals. In some embodiments,the display 208 includes an electronic display capable of outputtingvisual data to a user. For example, the display 208 may include, but isnot limited to, an LCD display, an LED display, an OLED display, aprojector, or similar display device capable of outputting images, text,or the like to a user. As another, non-limiting, example, the display208 may include a wearable display such as a smart watch, smart glasses,a heads-up display, or the like. Further, the display 208 may be acomponent of a smart phone, a personal digital assistant, a television,a table computer, a notebook (laptop) computer, a personal computer, avehicle dashboard, or the like.

In certain embodiments, the display 208 includes one or more speakersfor producing sound. For example, the display 208 may produce an audiblealert or notification (e.g., a beep or chime). In some embodiments, thedisplay 208 includes one or more haptic devices for producingvibrations, motion, or other haptic feedback. In some embodiments, allor portions of the display 208 may be integrated with the input device206. For example, the input device 206 and display 208 may form atouchscreen or similar touch-sensitive display. In other embodiments,the display 208 may be located near the input device 206.

The transmitter 210 is used to provide UL communication signals to thebase unit 104 and the receiver 212 is used to receive DL communicationsignals from the base unit 104. In one embodiment, the transmitter 210is used to transmit load information to the base unit 104. In certainembodiments, the receiver 212 may be used to detect a reference signaland/or to receive information. Although only one transmitter 210 and onereceiver 212 are illustrated, the remote unit 102 may have any suitablenumber of transmitters 210 and receivers 212. The transmitter 210 andthe receiver 212 may be any suitable type of transmitters and receivers.In one embodiment, the transmitter 210 and the receiver 212 may be partof a transceiver.

FIG. 3 depicts another embodiment of an apparatus 300 that may be usedfor enhanced measurements and filters. The apparatus 300 includes oneembodiment of the base unit 104. Furthermore, the base unit 104 mayinclude a processor 302, a memory 304, an input device 306, a display308, a transmitter 310, and a receiver 312. As may be appreciated, theprocessor 302, the memory 304, the input device 306, and the display 308may be substantially similar to the processor 202, the memory 204, theinput device 206, and the display 208 of the remote unit 102,respectively. In certain embodiments, the processor 302 may be used todetermine carriers to be used based on information received from aremote unit 102.

The transmitter 310 is used to provide DL communication signals to theremote unit 102 and the receiver 312 is used to receive UL communicationsignals from the remote unit 102. In one embodiment, the receiver 312 isused to receive information corresponding to load measurements from oneor more remote units 102. Although only one transmitter 310 and onereceiver 312 are illustrated, the base unit 104 may have any suitablenumber of transmitters 310 and receivers 312. The transmitter 310 andthe receiver 312 may be any suitable type of transmitters and receivers.In one embodiment, the transmitter 310 and the receiver 312 may be partof a transceiver.

FIG. 4 illustrates a graph 400 of one embodiment of layer 3 filtering.In the illustrated embodiment, RSRP 402 in the y-axis is illustratedover time 404 in the x-axis. Specifically, a mean RSRP 406 and afiltered RSRP 408 are illustrated over time 404. The filtered RSRP 408is calculated using the following formula: F_(n)=(1−a)F_(n-1)+aM_(n)where M_(n) is the latest received measurement result (e.g., measuredRSRP) from the physical layer; F_(n) is the updated filtered measurementresult (e.g., reported RSRP), that is used for evaluation of reportingcriteria or for measurement reporting; F_(n-1) is the old filteredmeasurement result, where F₀ is set to M₁ when the first measurementresult from the physical layer is received; and

${a = \frac{1}{2^{({k/4})}}},$where k is the filter coefficient for the corresponding measurementquantity.

The filtering formula, F_(n)=(1−a)F_(n-1)+aM_(n), assumes thatsuccessive physical layer measurements are available within a specifiedtime period (e.g., physical layer measurements occur at least once every200 ms when a UE is not in DRX). In certain embodiments for LAA, if thephysical layer measurement is not available (e.g., due to a discoverysignal not having been transmitted), the physical layer does not providethe M_(n) quantity mentioned above. When the UE does receive a discoverysignal at a later time, an M_(n) value is provided to the layer 3filter.

As may be appreciated, for purpose of illustration, RSRP values may begenerated as follows: durations between successive measurements may begenerated randomly based on a Gaussian distribution with a mean of 200ms and a standard deviation of 400 ms; a mean value of RSRP −90 dbm isselected and RSRP measurements are generated as Gaussian random sampleswith the chosen mean and a standard deviation of 4 db; if the durationbetween the n-th measurement occasion and the n+1-th measurementoccasion is more than a threshold value of 1000 ms, the mean value ofRSRP is changed as follows: with probability ⅓ the mean value of RSRPstays the same; with probability ⅓ it increases by 8 db and withprobability ⅓ it decreases by 8 db.

As may be appreciated, the purpose of filtering may be to avoid reactingto spikes in measurements (e.g., such as sending a measurement reportbased on measurements being temporarily much higher or lower).Accordingly, the efficacy of a filter may be measured in terms of howquickly it converges to mean values. The graph 400 shows the effect ofapplying the layer 3 filter of formula F_(n)=(1−a)F_(n-1)+aM_(n) with afilter-coefficient of 8 to RSRP measurements.

As illustrated, the layer 3 filter of formula F_(n)=(1−a)F_(n-1)+aM_(n)may not react quickly to measurements that have changed after a fairlylong duration of absence of discovery signals. Thus, althoughmeasurements may be too low, the UE may not trigger a measurement reportthereby resulting in radio link failures, handover failures, and soforth.

FIG. 5 illustrates a graph 500 of another embodiment of layer 3filtering. In the illustrated embodiment, RSRP 502 in the y-axis isillustrated over time 504 in the x-axis. Specifically, a mean RSRP 506and a filtered RSRP 508 are illustrated over time 504. The filtered RSRP508 is calculated using the following formula:F_(n)=(1−ã)F_(n-1)+ãM_(n), where M_(n) is the latest receivedmeasurement result (e.g., measured RSRP) from the physical layer; F_(n)is the updated filtered measurement result (e.g., reported RSRP), thatis used for evaluation of reporting criteria or for measurementreporting; F_(n-1) is the old filtered measurement result, where F₀ isset to M₁ when the first measurement result from the physical layer isreceived; ã=a if the time duration between M_(n) and M_(n-1) is lessthan a threshold duration (e.g. 1000 ms), and ã=1 otherwise (e.g., ifthe time duration between M_(n) and M_(n-1) is greater than or equal toa threshold duration);

${a = \frac{1}{2^{(\frac{k}{4})}}};$and k is the filter coefficient for the corresponding measurementquantity. As may be appreciated, the threshold duration may be signaledto a UE from an eNB. In some embodiments, ã=a if the time durationbetween M_(n) and M_(n-1) is less than or equal to a threshold duration(e.g. 1000 ms), and ã=1 otherwise (e.g., if the time duration betweenM_(n) and M_(n-1) is greater than a threshold duration).

Such a formula F_(n)=(1−ã)F_(n-1)+ãM_(n) may produce a simple forgettingfilter. In some embodiments, a simple forgetting filter may be producedby using the formula F_(n)=(1−a)F_(n-1)+aM_(n) where

${a = \frac{1}{2^{(\frac{\overset{\sim}{k}}{4})}}},$and a modified filter coefficient {tilde over (k)}=k if the timeduration between M_(n) and M_(n-1) is less than the threshold duration,and {tilde over (k)}=0 otherwise (e.g., if the time duration betweenM_(n) and M_(n-1) is greater than or equal to a threshold duration),where k is the filter coefficient for the corresponding measurementquantity. In some embodiments, {tilde over (k)}=k if the time durationbetween M_(n) and M_(n-1) is less than or equal to the thresholdduration, and {tilde over (k)}=0 otherwise (e.g., if the time durationbetween M_(n) and M_(n-1) is greater than a threshold duration), where kis the filter coefficient for the corresponding measurement quantity.

FIG. 5 illustrates the effect of using the simple forgetting filter onthe same RSRP measurements used to produce FIG. 4. It should be notedthat a threshold duration of 1000 ms is used. As illustrated by thefiltered RSRP 508, the simple forgetting filter reacts quickly tomeasurements that have changed after a fairly long duration of absenceof discovery signals. However, the filtered RSRP 508 may generatesignificant measurement spikes thereby resulting in excessivemeasurement reporting and handovers.

FIG. 6 illustrates a graph 600 of a further embodiment of layer 3filtering. In the illustrated embodiment, RSRP 602 in the y-axis isillustrated over time 604 in the x-axis. Specifically, a mean RSRP 606and a filtered RSRP 608 are illustrated over time 604. The filtered RSRP608 is calculated using the following formula:F_(n)=(1−ã)F_(n-1)+ãM_(n), where M_(n) is the latest receivedmeasurement result (e.g., measured RSRP) from the physical layer; F_(n)is the updated filtered measurement result (e.g., reported RSRP), thatis used for evaluation of reporting criteria or for measurementreporting; F_(n-1) is the old filtered measurement result, where F₀ isset to M₁ when the first measurement result from the physical layer isreceived;

${\overset{\sim}{a} = {a\frac{1}{1 + e^{({1 - \frac{t}{T}})}}}};$t is the time duration between M_(n) and M_(n-1); T is a thresholdduration (e.g. 1000 ms), which may be signaled to the UE;

${a = \frac{1}{2^{(\frac{k}{4})}}};$and k is the filter coefficient for the corresponding measurementquantity.

Such a formula F_(n)=(1−ã)F_(n-1)+ãM_(n) may produce a sigmoidforgetting filter. In some embodiments, a sigmoid forgetting filter maybe produced by using the formula F_(n)=(1−a)F_(n-1)+aM_(n) where

${a = \frac{1}{2^{(\frac{\overset{\sim}{k}}{4})}}},$and a modified filter coefficient {tilde over (k)}=k+4log₂(1+e^((1-t/T))), where k is the filter coefficient for thecorresponding measurement quantity.

FIG. 6 illustrates the effect of using the sigmoid forgetting filter onthe same RSRP measurements used to produce FIG. 4. It should be notedthat a threshold duration of 1000 ms is used. As illustrated by thefiltered RSRP 608, the sigmoid forgetting filter may not generatesignificant measurement spikes thereby inhibiting excessive measurementreporting and handovers.

In certain embodiments, a linear forgetting filter may be used. A linearforgetting filter may use the following formula:F_(n)=(1−ã)F_(n-1)+ãM_(n), where M_(n) is the latest receivedmeasurement result (e.g., measured RSRP) from the physical layer; F_(n)is the updated filtered measurement result (e.g., reported RSRP), thatis used for evaluation of reporting criteria or for measurementreporting; F_(n-1) is the old filtered measurement result, where F₀ isset to M₁ when the first measurement result from the physical layer isreceived;

${\overset{\sim}{a} = {\min\left( {1,{a\frac{\max\left( {t,T} \right)}{T}}} \right)}};$t is the time duration between M_(n) and M_(n-1); T is a thresholdduration (e.g. 1000 ms), which may be signaled to the UE;

${a = \frac{1}{2^{(\frac{k}{4})}}};$and k is the filter coefficient for the corresponding measurementquantity.

Other similar embodiments may generalize the sigmoid and linearforgetting filter embodiments. Such embodiments may include choosingother functions for ã. For example, ã could be chosen such that ã=aH(t)where H(t) is a mathematical function of such t that H(t) increases withincreasing values of t. Additionally, H(t) can be chosen such that H(t)has values between 0 and 1 for all values of t.

FIG. 7 illustrates a graph 700 of various embodiments of measurementadaptations. In the illustrated embodiment, probability (“P”)[xparameter <x value] 702 in the y-axis is illustrated over P[measurementwhen channel busy] 704 in the x-axis. Specifically, a P that a channelis busy when using periodic measurements 706, uniformly distributedrandom measurements 708, adaptive measurements 710, and an actual P thata channel is busy 712 are illustrated.

As may be appreciated, RSSI may be used to estimate a load on carriers.Moreover, a UE may report RSSI measurements for one or more LAAcarriers. Thus, a network (e.g., eNB) may be enabled to choose whetherand which carriers to configure as LAA carriers for the UE. RSSImeasurements may also be used to determine when to remove a carrier (dueto excessive load from other nodes). Consequently, the measured RSSI maybe used to capture a time-varying load on the carrier.

In various configurations, the UE may perform measurements on discoverysignals within periodically occurring DMTC time windows. A DMTC timewindow may be a time duration during which all discovery signals (e.g.,from the serving and neighbor LAA eNBs) are expected to be transmitted.That is, for example, the UE may perform measurements (e.g., RSSI and soforth) every 40 ms, which are then averaged and/or filtered. Theperiodic measurement may not enable the UE to obtain measurements thatare representative of the time-varying load on the carrier, such asbecause measuring RSSI during the DMTC time windows may result in anRSSI that indicates a load that is higher than the actual load on thecarrier.

Moreover, in certain embodiments, RSSI measurements may not be performedduring DMTC time windows. As may be appreciated, a UE may have gaps forperforming measurements on “inter-frequency” LAA carriers—i.e., carrierswithout configured secondary cells. If the UE uses gaps to performLAA-RSSI measurements, the network may configure specific subframesduring which the LAA-RSSI measurements occur. In various embodiments,LAA-RSSI measurements may be configured in addition to RSRP measurementsfor a carrier. Therefore, in order to reduce the number of times the UEswitches between monitoring the DL and performing a measurement,LAA-RSSI measurements may occur immediately adjacent to the DMTCwindows. As may be appreciated, this may provide a benefit of not havingto explicitly configure the LAA-RSSI measurement gaps.

In some embodiments, LAA-RSSI measurement gaps may be used and may occurimmediately before or immediately after RSRP measurement gaps. When a UEdoes not need a measurement gap to perform a measurement on an LAAcarrier, the measurement can occur when the carrier is busy (due totransmissions from either the serving LAA eNB or from another node) orwhen the channel is idle. Measurements may be considered to berepresentative of load on the channel, if the proportion of measurementsthat occur when the channel is busy is roughly the same as theproportion of time that the channel is busy. As may be appreciated, RSSImeasurements may be considered to be representative of load on a channelif: P[Measurement occurs when Channel is Busy]−P[Channel is busy]<ϵ, forsome small ϵ.

To get more representative RSSI measurements than may be obtained withperiodic measurements, the UE may perform continuous measurements of thechannel or perform measurements at random occasions. As may beappreciated, performing continuous measurements of a channel may consumea large amount of power; therefore, performing measurements at randomoccasions may be preferred because less power is consumed.

In one example of obtaining representative RSSI measurements, considerpacket arrival having a Poisson distribution with an inter-arrival timeof 40 ms. Each packet may be assumed to be 10 ms long. For transmissionover the channel, it may be assumed that the packet is transmitted in 1ms blocks which are separated in time by 8 ms. Periodic and randommeasurements may be compared in such an example. For periodicmeasurements, the measurement periodicity may be 40 ms and the durationof the measurement may be 1 ms. For the random measurements, themeasurement duration may be 1 ms, and the duration between the start ofthe measurements may be a uniformly distributed random variable between10 and 70 ms. The measurement parameters may be chosen such that the UEspends the substantially the same percentage of time on measurements inboth approaches. FIG. 7 shows a CDF of the probability that measurementoccurs when the channel is busy for periodic measurements 706 anduniformly distributed random measurements 708, and the probability thatthe channel is busy 712.

As can be seen, uniformly distributed random measurements 708 providesome advantages over periodic measurements 706. Specifically, the valueof P[Measurement occurs when Channel is Busy]−P[Channel is busy] issmaller for the uniformly distributed random measurements 708 comparedto that for the periodic measurements 706.

The probability that a channel is busy when using adaptive measurements710 is also illustrated. One embodiment of an approach for usingadaptive measurements 710 is explained forthwith. Specifically,occasions (e.g., time windows) where the UE performs measurements arechosen randomly, as follows: 1) Two measurement periodicities areconfigured at the UE. The first is a “quiet channel periodicity” (e.g.,quite channel inter-measurement duration) and the second is a “busychannel periodicity” (e.g., busy channel inter-measurement duration).The quiet channel periodicity is longer than the busy channelperiodicity. The UE is also configured with separate measurementdurations for busy and quiet periods. Additionally, the UE is configuredwith a busyOverhang integer parameter; 2) During a measurement occasion,if the channel is determined to be busy, the UE uses the busy channelperiodicity to determine an occasion in the future to perform the nextmeasurement. For example, the next occasion may be determined based onan exponential distribution with a mean equal to the busy channelperiodicity. Alternatively, the next occasion may be based on thecurrent time plus the busy channel periodicity; and 3) If the channel isdetermined to be not busy, the UE starts a counter that is set to thevalue of the busyOverhang integer. The UE then selects the nextmeasurement occasion based on the busy channel periodicity, as describedabove. At each measurement occasion, that follows: a) If the channel isnot busy, the UE decrements the counter by 1. If the counter reaches 0,the UE uses the quiet channel periodicity for future measurementsoccasions (until the channel is determined to be busy); and b) If thechannel is busy, the UE uses the busy channel periodicity. In oneembodiment, a quiet channel periodicity may be 200 ms and a busy channelperiodicity may be 8 ms, while in other embodiments the quiet channelperiodicity and the busy channel periodicity may be any suitable value.Furthermore, in one embodiment, a measurement duration during quietperiods may be 6 ms and a measurement duration during busy periods maybe 1 ms, while in other embodiments, the measurement durations may beany suitable values.

FIG. 7 shows how the probability that measurement occurs when thechannel is busy using adaptive measurements 710 may be closer to theprobability that the channel is busy 712 than the probability thatmeasurement occurs when the channel is busy for periodic measurements706 and uniformly distributed random measurements 708.

It should be noted that in certain LTE systems a UE computes an RSSImetric as part of RSRQ computation. RSSI may be defined as including thelinear average of the total received power (in [W]) observed only incertain OFDM symbols of measurement subframes, in the measurementbandwidth over N number of resource blocks by the UE from all sources,including co-channel serving and non-serving cells, adjacent channelinterference, thermal noise, etc. In this disclosure, a new measurementquantity is defined that is not restricted to OFDM symbols ofmeasurement subframes because, for example, there may not even be areference symbol or signal transmission present when a UE performs sucha measurement. The new measurement quantity may be referred to asLAA-RSSI, energy measurement, and/or a carrier loading measurement.

A duration of an LAA-RSSI measurement (e.g., Xwin) may be less than orequal to five subframes. In certain embodiments, the duration of anLAA-RSSI measurement may be one or two subframes to reduce UE powerconsumption. The duration of the LAA-RSSI measurement may be set via RRCconfiguration.

A location of an LAA-RSSI measurement may be in any suitable location.For example, an LAA-RSSI measurement may be in any of the followinglocations: within DMTC occasions (e.g., time windows) of a UE; and inseparate LAA-RSSI occasions, as explained in greater detail below.

LAA-RSSI measurements may be performed within DMTC occasions of a UE. Asmay be appreciated, DMTC occasions are 6 ms long and may occur with aconfigurable periodicity (e.g., 10 ms, 20 ms, 40 ms, 80 ms, 160 ms, andso forth). In certain embodiments, UEs may measure RSRP and/or RSRQafter detecting discovery signals within a configured DMTC occasion. ForLAA embodiments, the UE may measure LAA-RSSI within each DMTC occasion,or within a subset of the DMTC occasions. For example, DMTC periodicitymay be configured to be 40 ms while LAA-RSSI measurement periodicity maybe configured as 640 ms. In this example, a UE measures LAA-RSSI every16th DMTC occasion. The exact subframes that the UE uses for LAA-RSSImeasurement may be determined via higher layer configuration (e.g., asubframe offset related to LAA-RSSI measurement from the start of a DMTCoccasion where LAA-RSSI is measured), via a UE autonomously picking thesubframes from within the DMTC occasion, via a specification, and soforth. As may be appreciated, higher layer configuration may beconfiguration information received from messaging at the RRC layer, theMAC layer, or any other suitable layer. Moreover, higher layer signalingmay be messaging at the RRC layer, the MAC layer, or any other suitablelayer.

Taking LAA-RSSI measurements within DMTC occasions of a UE may beadvantageous because a UE has to wake up during DMTC occasions for othermeasurements such as RSRP and RSRQ and performing LAA-RSSI measurementsat the same time may result in relatively smaller additional powerconsumption for the UE.

LAA-RSSI measurements may be performed in separate LAA-RSSI occasions.In such LAA-RSSI occasions, each LAA-RSSI occasion may be a window of K(e.g., K>=Xwin, K>=5 subframes) subframes. Within each LAA-RSSIoccasion, the exact subframes that the UE uses for LAA-RSSI measurement(e.g., for the case where K>=Xwin) may be determined from higher layerconfiguration (e.g., a subframe offset related to LAA-RSSI measurementfrom the start of an LAA-RSSI occasion), from the UE autonomouslypicking the subframes, via specification, and so forth. Moreover, thestart of each LAA-RSSI occasion may be determined from one of thefollowing: LAA-RSSI occasions may start immediately before or after eachDMTC occasion or a subset of DMTC occasions configured for the UE;LAA-RSSI occasions may start immediately following L1 offset subframesafter each DMTC occasion or a subset of DMTC occasions for the UE; andthe UE may be configured via higher layers with an LAA-RSSI-periodicityand an LAA-RSSI offset, which are explained in greater detail below.

LAA-RSSI occasions may start immediately before or after each DMTCoccasion or a subset of DMTC occasions configured for the UE. Morespecifically, a UE may be configured via higher layers with thefollowing parameters a DMTC-periodicity, a DMTC-offset, and optionallyan LAA-RSSI-periodicity. The first subframe of each LAA-RSSI occasionoccurs at a SFN and subframe of the PCell meeting the followingconditions: SFN mod T=FLOOR (DMTC-offset/10); subframe=DMTC-offset mod10+L0 offset; with T=LAA-RSSI-periodicity/10 (if configured withLAA-RSSI-periodicity), or T=DMTC-periodicity/10 (if not configured withLAA-RSSI-periodicity); and L0 offset=6. With some example parametersettings, the above equations may lead to the following behavior. If aUE is configured with a DMTC-periodicity of 40 ms and DMTC-offset is 0,DMTC occasions for the UE are subframes [0 to 5], [40 to 45], [80-85],and so forth. If the LAA-RSSI periodicity is also 40 ms, the LAA-RSSIoccasions for the UE then start in subframes 6, 46, 86, and so forth. Ifthe LAA-RSSI periodicity is 80 ms, the LAA-RSSI occasions for the UEthen start in subframes 6, 86, and so forth.

LAA-RSSI occasions may start immediately following L1 offset subframesafter each DMTC occasion or a subset of DMTC occasions for the UE. L1offset may be a pseudo-random offset generated by a UE with thefollowing characteristics. L1 offset <P1. In one example,P1=DMTC-periodicity minus the duration of a DMTC occasion. In anotherexample, P1=DMTC-periodicity minus the duration of a DMTC occasion minusthe duration of an LAA-RSSI occasion. The starting seed for thepseudo-random number generator generating the L1 offset may be afunction of one or more of the following: the PCID of the serving cellto which the UE reports its LAA-RSSI measurement, C-RNTI of the UE, SFNof the corresponding DMTC occasion, and a parameter configured by higherlayers (e.g., a DMRS scrambling sequence initialization value, a virtualcell ID, and so forth).

More specifically, a UE may be configured via higher layers with thefollowing parameters: a DMTC-periodicity, a DMTC-offset, and optionallyan LAA-RSSI-periodicity. The first subframe of each LAA-RSSI occasionoccurs at a SFN and subframe of the PCell meeting the followingconditions: SFN mod T=FLOOR (DMTC-offset/10); subframe=DMTC-offset mod10+(L1 offset(SFN))mod(P1); and with T=LAA-RSSI-periodicity/10 (ifconfigured with LAA-RSSI-periodicity), or T=DMTC-periodicity/10 (if notconfigured with LAA-RSSI-periodicity). For example, L1 offset(SFN)=(A*L1 offset (SFN−1))mod(D); where A and D are any two largerelatively prime numbers (e.g., A=39827; D=65537; L1 offset(−1)=nRNTIwhich is the Ue's C-RNTI. In this example, a separate L1 offset isdetermined for each SFN and the seed for generating pseudo-random valuesof L1 offset is the UE's C-RNTI. As previously discussed, the seed mayinstead be based on PCID, or other higher layer configured parameters.

The UE may be configured via higher layers with an LAA-RSSI-periodicityand an LAA-RSSI offset. LAA-RSSI occasions may be determined from theseparameters (e.g., they are independently configured from DMTCoccasions). The first subframe of each LAA-RSSI occasion occurs at anSFN and subframe of the PCell meeting the following conditions: SFN modT=FLOOR (LAA-RSSI-offset/10); subframe=LAA-RSSI-offset mod 10; andT=LAA-RSSI-periodicity/10.

In certain embodiments, a UE may report the percent of time that thediscovery signal was delayed as an indication of load. Moreover, incertain embodiments, there may be independent filtering of two RSSIbins: one bin is above a threshold (e.g., an occupancy RSSI), and theother is below the threshold. The filtering may use shorter termaveraging (e.g., first filter) for the first bin and longer termaveraging (e.g., second filter) for the second bin.

FIG. 8 is a schematic flow chart diagram illustrating one embodiment ofa method 800 for enhanced filtering. In some embodiments, the method 800is performed by an apparatus, such as the remote unit 102. In certainembodiments, the method 800 may be performed by a processor executingprogram code, for example, a microcontroller, a microprocessor, a CPU, aGPU, an auxiliary processing unit, a FPGA, or the like.

The method 800 may include detecting 802 a reference signal during afirst time window of a set of time windows during which reception of thereference signal is expected. In some embodiments, the remote unit 102(e.g., the transmitter 210) may detect 802 the reference signal duringthe first time window of the set of time windows during which receptionof the reference signal is expected.

The method 800 may include detecting 804 the reference signal during asecond time window of the set of time windows. The second time windowoccurs an offset time after the first time window. In certainembodiments, the remote unit 102 may detect 804 the reference signalduring the second time window of the set of time windows. The offsettime may include one or more time windows of the set of time windowsduring which the reference signal is not detected.

The method 800 may also include determining 806 a filter coefficientbased on the offset time, then the method 800 may end. The filtercoefficient is used to generate a filtered measurement. In certainembodiments, the remote unit 102 may determine 806 the filtercoefficient based on the offset time. In some embodiments, determining806 the filter coefficient based on the offset time includes determiningthe filter coefficient by summing a predetermined filter coefficient anda parameter derived as a function of the offset time. In variousembodiments, determining 806 the filter coefficient based on the offsettime includes determining the filter coefficient to be a first value ifthe offset time is less than a threshold time and to be a second valueif the offset time is greater than or equal to the threshold time.

FIG. 9 is a schematic flow chart diagram illustrating one embodiment ofa method 900 for enhanced measurements. In some embodiments, the method900 is performed by an apparatus, such as the remote unit 102. Incertain embodiments, the method 900 may be performed by a processorexecuting program code, for example, a microcontroller, amicroprocessor, a CPU, a GPU, an auxiliary processing unit, a FPGA, orthe like.

The method 900 may include performing 902 a first measurement at a firsttime. In certain embodiments, a remote unit 102 may perform 902 thefirst measurement at the first time. The method 900 may also includedetermining 904 an offset time selected pseudo-randomly from a set ofvalues. In one embodiment, the remote unit 102 may determine 904 theoffset time selected pseudo-randomly from the set of values. In oneembodiment, determining 904 the offset time selected pseudo-randomlyfrom the set of values includes determining the offset time based on atleast one of a subframe index, a system frame number, a C-RNTI, aphysical cell id, a virtual cell id, and a scrambling sequenceinitialization value. In another embodiment, determining 904 the offsettime selected pseudo-randomly from the set of values includesdetermining the offset time based on a modulo function with at least oneof the following inputs: a subframe index, a system frame number, a cellradio network temporary identifier (“C-RNTI”), a physical cell id, avirtual cell id, and a scrambling sequence initialization value.

The method 900 may include performing 906 a second measurement at asecond time, the second time being the offset time after the first time.The second measurement is used for a carrier loading measurement. Thenthe method 900 may end. In certain embodiments, the remote unit 102 mayperform 906 the second measurement at the second time.

FIG. 10 is a schematic flow chart diagram illustrating anotherembodiment of a method 1000 for enhanced measurements. In someembodiments, the method 1000 is performed by an apparatus, such as theremote unit 102. In certain embodiments, the method 1000 may beperformed by a processor executing program code, for example, amicrocontroller, a microprocessor, a CPU, a GPU, an auxiliary processingunit, a FPGA, or the like.

The method 1000 may include performing 1002 a first measurement in afirst set of subframes at a first time. The first set of subframesincludes at least one subframe. In certain embodiments, a remote unit102 may perform 1002 the first measurement in the first set of subframesat the first time. The method 1000 may also include performing 1004 asecond measurement in a second set of subframes at a second time, thenthe method 1000 may end. The second set of subframes includes at leastone subframe. In one embodiment, the remote unit 102 may perform 1004the second measurement in the second set of subframes at the secondtime.

The second set of subframes is offset in time from the first set ofsubframes by an offset time. The offset time is determined using apseudo-random function. In one embodiment, the pseudo-random functiondetermines the offset time based on at least one of a subframe index, asystem frame number, a cell radio network temporary identifier(“C-RNTI”), a physical cell id, a virtual cell id, and a scramblingsequence initialization value. In some embodiments, the firstmeasurement is an RSRP measurement and the second measurement is acarrier loading measurement. In various embodiments, the firstmeasurement occurs in a DMTC time window and the second measurementoccurs outside of a DMTC time window.

FIG. 11 is a schematic flow chart diagram illustrating one embodiment ofa method 1100 for carrier determination. In some embodiments, the method1100 is performed by an apparatus, such as the base unit 104. In certainembodiments, the method 1100 may be performed by a processor executingprogram code, for example, a microcontroller, a microprocessor, a CPU, aGPU, an auxiliary processing unit, a FPGA, or the like.

The method 1100 may include receiving 1102 information corresponding toload measurements made by a device (e.g., the remote unit 102). The loadmeasurements may include a first measurement in a first set of subframesat a first time. The first set of subframes includes at least onesubframe. The load measurements may also include a second measurement ina second set of subframes at a second time. The second set of subframesincludes at least one subframe. The second set of subframes is offset intime from the first set of subframes by an offset time. The offset timeis determined using a pseudo-random function. In certain embodiments, abase unit 104 may receive 1102 the information corresponding to the loadmeasurements. The method 1100 may also include determining 1104 carriersto be used based on the information, then the method 1100 may end. Inone embodiment, the base unit 104 may determine 1104 the carriers to beused based on the information.

In some embodiments, the first measurement is an RSRP measurement andthe second measurement is a carrier loading measurement. In variousembodiments, the first measurement occurs in a DMTC time window and thesecond measurement occurs outside of a DMTC time window.

FIG. 12 is a schematic flow chart diagram illustrating a furtherembodiment of a method 1200 for enhanced measurements. In someembodiments, the method 1200 is performed by an apparatus, such as theremote unit 102. In certain embodiments, the method 1200 may beperformed by a processor executing program code, for example, amicrocontroller, a microprocessor, a CPU, a GPU, an auxiliary processingunit, a FPGA, or the like.

The method 1200 may include receiving 1202 a DMTC from higher layersignaling. In certain embodiments, a remote unit 102 may receive 1202the DMTC from higher layer signaling. The method 1200 may also includedetermining 1204 a set of periodic DMTC time windows from the receivedDMTC. Each periodic DMTC time window of the set of periodic DMTC timewindows includes a set of contiguous subframes. In one embodiment, theremote unit 102 may determine 1204 the set of periodic DMTC time windowsfrom the received DMTC.

The method 1200 may include determining 1206 a set of carrier loadingmeasurement time windows. Each carrier loading measurement time windowof the set of carrier loading measurement time windows includes a set ofcontiguous subframes. In one embodiment, the remote unit 102 maydetermine 1206 the set of carrier loading measurement time windows.

The method 1200 may include measuring 1208 carrier loading in at leastone subframe in each carrier loading measurement time window of the setof carrier loading measurement time windows. Then the method 1200 mayend. In certain embodiments, the remote unit 102 may measure 1208carrier loading in at least one subframe in each carrier loadingmeasurement time window of the set of carrier loading measurement timewindows.

Each carrier loading measurement time window of the set of the carrierloading measurement time windows occurs immediately adjacent in time toa respective periodic DMTC time window of the set of periodic DMTC timewindows and each carrier loading measurement time window does notoverlap its respective periodic DMTC time window.

In one embodiment, the method includes measuring at least one ofreference signal received power (“RSRP”) and reference signal receivedquality (“RSRQ”) in at least one subframe of each periodic DMTC timewindow of the set of periodic DMTC time windows. In certain embodiments,each carrier loading measurement time window of the set of carrierloading measurement time windows is a periodic carrier loadingmeasurement time window. In certain embodiments, a carrier loadingmeasurement time window periodicity is a multiple of a DMTC time windowperiodicity.

Embodiments may be practiced in other specific forms. The describedembodiments are to be considered in all respects only as illustrativeand not restrictive. The scope of the invention is, therefore, indicatedby the appended claims rather than by the foregoing description. Allchanges which come within the meaning and range of equivalency of theclaims are to be embraced within their scope.

The invention claimed is:
 1. An apparatus comprising: a receiver that:detects a reference signal during a first time window of a plurality oftime windows during which reception of the reference signal is expected;and detects the reference signal during a second time window of theplurality of time windows, wherein the second time window occurs anoffset time after the first time window; and a processor that determinesa filter coefficient based on the offset time, wherein the filtercoefficient is used to generate a filtered measurement, the processordetermines the filter coefficient by summing a predetermined filtercoefficient and a parameter derived as a function of the offset time,and the filter coefficient is used in a sigmoid forgetting filter. 2.The apparatus of claim 1, wherein the offset time comprises one or moretime windows of the plurality of time windows during which the referencesignal is not detected.
 3. The apparatus of claim 1, wherein theprocessor determines the filter coefficient to be a first value if theoffset time is less than a threshold time and to be a second value ifthe offset time is greater than or equal to the threshold time.
 4. Theapparatus of claim 1, wherein the filtered measurement is determinedbased on a previous filtered measurement and a measurement of thereference signal during the second time window.
 5. The apparatus ofclaim 4, wherein the filtered measurement is determined by equation(1−a)F_(n-1)+aM_(n), wherein F_(n-1) is the previous filteredmeasurement, M_(n) is the measurement of the reference signal during thesecond time window, and a is a parameter derived from the filtercoefficient.
 6. The apparatus of claim 5, wherein the parameter aderived from the filter coefficient is determined by equation${a = \frac{1}{2^{(\frac{\overset{\sim}{k}}{4})}}},$ where {tilde over(k)} is the filter coefficient.
 7. The apparatus of claim 6, wherein thefilter coefficient {tilde over (k)} is determined by the equation {tildeover (k)}=k+4 log₂(1+e^((1-t/T))), where k is a predetermined filtercoefficient for the corresponding measurement quantity, t is the offsettime; T is a threshold duration.
 8. A method comprising: detecting, byuse of a receiver, a reference signal during a first time window of aplurality of time windows during which reception of the reference signalis expected; detecting the reference signal during a second time windowof the plurality of time windows, wherein the second time window occursan offset time after the first time window; and determining a filtercoefficient based on the offset time, wherein the filter coefficient isused to generate a filtered measurement, determining the filtercoefficient based on the offset time comprises determining the filtercoefficient by summing a predetermined filter coefficient and aparameter derived as a function of the offset time, and the filtercoefficient is used in a sigmoid forgetting filter.
 9. The method ofclaim 8, wherein the filtered measurement is determined based on aprevious filtered measurement and a measurement of the reference signalduring the second time window.
 10. The method of claim 9, wherein thefiltered measurement is determined by equation (1−a)F_(n-1)+aM_(n),wherein F_(n-1) is the previous filtered measurement, M_(n) is themeasurement of the reference signal during the second time window, and ais a parameter derived from the filter coefficient.
 11. The method ofclaim 8, wherein the offset time comprises one or more time windows ofthe plurality of time windows during which the reference signal is notdetected.
 12. The method of claim 8, wherein determining the filtercoefficient based on the offset time comprises determining the filtercoefficient to be a first value if the offset time is less than athreshold time and to be a second value if the offset time is greaterthan or equal to the threshold time.
 13. A method comprising: detecting,by use of a receiver, a reference signal during a first time window of aplurality of time windows during which reception of the reference signalis expected; detecting the reference signal during a second time windowof the plurality of time windows, wherein the second time window occursan offset time after the first time window; and determining a filteredmeasurement based on a previous filtered measurement and a filterparameter, wherein the filter parameter is derived based on the offsettime, the filter parameter is determined as a product of a predeterminedfilter parameter and a result of a mathematical function of the offsettime, and the filter coefficient is used in a sigmoid forgetting filter.14. The method of claim 13, wherein the result of the mathematicalfunction of the offset time increases toward 1 as the offset timeincreases.
 15. The method of claim 13, wherein the offset time comprisesone or more time windows of the plurality of time windows during whichthe reference signal is not detected.
 16. The method of claim 13,wherein the filtered measurement is determined by equation(1−a)F_(n-1)+aM_(n), wherein F_(n-1) is the previous filteredmeasurement, M_(n) is the measurement of the reference signal during thesecond time window, and a is a parameter derived from the filtercoefficient.
 17. The method of claim 13, comprising determining thefilter parameter to be a first value if the offset time is less than athreshold time and to be a second value if the offset time is greaterthan or equal to the threshold time.